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Microsoft DP-100 Exam Dumps

Exam Name: Designing and Implementing a Data Science Solution on Azure Exam
Certification Name: Microsoft Azure

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  • Total Questions: 354
  • Last Updation Date: 8-Sep-2023

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You are a lead data scientist for a project that tracks the health and migration of birds. You create a multi-class
image classification deep learning model that uses a set of labeled bird photographs collected by experts. You have 100,000 photographs of birds. All photographs use the JPG format and are stored in an Azure blob container in an Azure subscription. You need to access the bird photograph files in the Azure blob container from the Azure Machine Learning service workspace that will be used for deep learning model training. You must minimize data movement. What should you do?

 

Create an Azure Data Lake store and move the bird photographs to the store.

 

Create an Azure Cosmos DB database and attach the Azure Blob containing bird photographs storage to the database.

 

Create and register a dataset by using TabularDataset class that references the Azure blob storage containing bird photographs

 

Register the Azure blob storage containing the bird photographs as a datastore in Azure Machine
Learning service

 

Copy the bird photographs to the blob datastore that was created with your Azure Machine Learning service workspace


Register the Azure blob storage containing the bird photographs as a datastore in Azure Machine
Learning service


Explanation
We recommend creating a datastore for an Azure Blob container. When you create a workspace, an Azure
blob container and an Azure file share are automatically registered to the workspace.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-access-data





You use Azure Machine Learning designer to create a training pipeline for a regression model. You need to prepare the pipeline for deployment as an endpoint that generates predictions asynchronously for a dataset of input data values. What should you do?

 

You need to prepare the pipeline for deployment as an endpoint that generates predictions 

 

asynchronously for

 

a dataset of input data values.

 

What should you do?


a dataset of input data values.


Explanation
You must first convert the training pipeline into a real-time inference pipeline. This process removes training
modules and adds web service inputs and outputs to handle requests.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/tutorial-designer-automobile-price-deploy
https://docs.microsoft.com/en-us/azure/machine-learning/algorithm-module-reference/enter-data-manually





You are developing a deep learning model by using TensorFlow. You plan to run the model training workload
on an Azure Machine Learning Compute Instance.
You must use CUDA-based model training.
You need to provision the Compute Instance.
Which two virtual machines sizes can you use? To answer, select the appropriate virtual machine sizes in the
answer area.NOTE: Each correct selection is worth one point.



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